{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9854261","patent":{"patent_number":"US-9854261","title":"Detecting markers in an encoded video signal","assignee":null,"inventors":[],"filing_date":"2015-01-06T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["H04N","H04N"],"num_claims":20,"abstract":"A video decoding method is implemented by a computer having multiple parallel processing units. A stream of data elements is received, some of which encode video content. The stream comprises marker sequences, each marker sequence comprising a marker which does not encode video content. A known pattern of data elements occurs in each marker sequence. A respective part of the stream is supplied to each parallel processing unit. Each parallel processing unit processes the respective part of the stream, whereby multiple parts of the stream are processed in parallel, to detect whether any of the multiple parts matches the known pattern of data elements, thereby identifying the markers. The encoded video content is separated from the identified markers. The separated video content is decoded, and the decoded video content outputted on a display."},"analysis":{"summary":"Detecting Markers in an Encoded Video Signal introduces an innovative approach to video decoding, significantly improving efficiency and reducing processing bottlenecks. The core innovation lies in the method's ability to identify and separate marker sequences within a video stream using multiple parallel processing units. This is achieved by dividing the stream and supplying a part to each processing unit, each tasked with detecting a known pattern of data elements indicating a marker. Once identified, the encoded video content is separated from the markers and decoded, outputting the decoded video on a display.\n\nThis technology addresses the problem of inefficient video decoding caused by the overhead of identifying non-video data. By distributing the marker detection task across multiple processing units, the system achieves faster and more efficient decoding. This approach reduces the computational burden on individual processing units, leading to smoother video playback and enhanced user experiences.\n\nThe business value of this patent lies in its potential to improve video streaming services, digital television, and video editing software. The enhanced decoding efficiency enables the delivery of higher-resolution video content to a wider range of devices, while also reducing power consumption. This makes it particularly valuable for mobile devices and other battery-powered applications.\n\nThe market opportunity for this technology is substantial, as video continues to dominate our digital lives. The demand for high-quality video content is constantly growing, and innovations like Detecting Markers in an Encoded Video Signal will play a crucial role in shaping the future of video processing. The technology has the potential to be integrated into various video platforms and devices, creating significant revenue opportunities for its developers and licensees.","layman_explanation":"Detecting Markers in an Encoded Video Signal addresses the challenge of efficiently decoding video content by streamlining the process of identifying and separating non-video data. In essence, it's like having a highly skilled editor who can quickly remove unnecessary elements from a video file, allowing the core content to be processed more efficiently.\n\n1. What Problem Does This Solve? (100-150 words)\nVideo files often contain additional data, such as markers or metadata, that are not part of the actual video content. Traditional video decoding methods can struggle with the task of distinguishing between video content and non-video data, leading to computational inefficiencies and slower processing times. This can result in buffering, lag, and a suboptimal viewing experience. Existing solutions often lack the ability to efficiently identify and separate these non-video elements, leading to performance bottlenecks.\n\n2. How Does It Work? (200-300 words)\nDetecting Markers in an Encoded Video Signal employs a parallel processing approach to identify and separate marker sequences within a video stream. Imagine a team of workers, each assigned to a specific section of a video file. Each worker is trained to recognize a specific pattern, indicating the presence of a marker. By working simultaneously, the team can quickly identify all the markers within the video file. Once the markers are identified, they are separated from the video content, allowing the core content to be processed more efficiently. This process is analogous to removing the commercials from a television broadcast, allowing viewers to focus solely on the program they want to watch. The key is that multiple processors handle different parts of the stream at the same time.\n\n3. Why Does This Matter? (150-200 words)\nThe market impact of this technology is significant, as it has the potential to improve video playback performance across a wide range of devices and platforms. By reducing processing times and minimizing buffering, this innovation can enhance the user experience and enable the delivery of higher-resolution video content. The competitive advantages stem from the technology's ability to optimize resource utilization and minimize unnecessary computations. This can lead to increased efficiency, reduced power consumption, and improved overall performance. The potential ROI and business value are substantial, as the technology can be licensed to video streaming providers, digital television operators, and video editing software developers.\n\n4. What's Next? (50-100 words)\nThe future applications of this technology are vast, ranging from improved video streaming services to enhanced digital television and video editing software. The market adoption timeline is expected to be relatively rapid, as the technology can be easily integrated into existing video platforms and devices. The investment implications are promising, as the technology has the potential to generate significant revenue streams through licensing and integration agreements.","technical_analysis":"Detecting Markers in an Encoded Video Signal provides a method for enhanced video decoding using parallel processing. The technical architecture involves several key stages: data stream reception, stream division, parallel processing, marker detection, content separation, and video decoding. The incoming video stream is divided and distributed among multiple parallel processing units. Each unit independently analyzes its portion of the stream to detect marker sequences, which are non-video data elements with a known pattern.\n\nThe marker detection process involves comparing the data elements in each processing unit's stream portion against a predefined marker pattern. Upon detection of a marker, the system separates the encoded video content from the identified marker. This separation ensures that only relevant video data is passed on for decoding, minimizing unnecessary computations. The separated video content is then decoded using a standard video decoder, and the decoded video is outputted on a display.\n\nThe implementation details focus on optimizing the marker detection algorithm and managing the parallel processing units. The marker pattern must be chosen carefully to ensure accurate detection while minimizing false positives. The distribution of the video stream among the processing units must be balanced to maximize parallel processing efficiency. Synchronization and communication protocols are crucial for coordinating the parallel processing units and ensuring data integrity.\n\nIntegration patterns involve incorporating this technology into existing video decoding pipelines. The system can be implemented as a hardware accelerator or as a software module within a video decoding application. Performance characteristics are significantly improved due to the parallel processing approach, resulting in faster decoding times and reduced latency.\n\nCode-level implications involve optimizing the marker detection algorithm for parallel execution and managing memory allocation across the processing units. The choice of programming language and libraries can also impact performance. Overall, Detecting Markers in an Encoded Video Signal offers a technically sound approach to improving video decoding efficiency through parallel processing and marker detection.","business_analysis":"Detecting Markers in an Encoded Video Signal presents a significant business opportunity within the video processing and streaming industry. The market opportunity size is substantial, given the ever-increasing demand for high-quality video content across various platforms and devices. The competitive advantages stem from the enhanced decoding efficiency and reduced processing bottlenecks offered by this technology.\n\nThe revenue potential is multifaceted. Licensing the technology to video streaming providers, digital television operators, and video editing software developers can generate substantial revenue streams. Integrating the technology into hardware devices, such as smartphones and smart TVs, can create a competitive edge and increase sales. Offering cloud-based video processing services that leverage this technology can attract a wide range of customers.\n\nThe business models can include licensing fees, subscription fees, and revenue sharing agreements. Strategic positioning involves targeting key players in the video industry and establishing partnerships with hardware manufacturers. The return on investment (ROI) projections are promising, given the potential for increased revenue, reduced operating costs, and enhanced customer satisfaction.\n\nDetecting Markers in an Encoded Video Signal offers a compelling value proposition for businesses operating in the video ecosystem. Its ability to improve video playback performance, reduce power consumption, and enable the delivery of higher-resolution content positions it as a key enabler for the future of video processing. The commercial applications are vast, ranging from video streaming services to digital television and video editing software. This technology has the potential to transform the way video content is processed and delivered, creating significant business opportunities for its developers and licensees.","faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Detecting markers in an encoded video signal","description":"A video decoding method is implemented by a computer having multiple parallel processing units. A stream of data elements is received, some of which encode video content. The stream comprises marker s","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9854261","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9854261","citation_suggestion":"Patentable. \"Detecting markers in an encoded video signal\" (US-9854261). https://patentable.app/patents/US-9854261","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9854261","json":"https://patentable.app/api/llm-context/US-9854261","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T07:43:28.348Z"}